Mobility as a Service Concept

With the increasing possibilities of information technology that is becoming mobile accessible, geo-specific and real-time, we are seeing an increase in the variety of different mobility services. New technologies and business models are evolving, and changing how we use the transport system, and how it is being provided.

• Shared modes provide “short term access” to various types of transport mode as and when the user requires them (depending on availability).

• But they can sometimes be seen as competing with public transport.

• Shared modes can be used effectively to reduce the first/last mile problem.

• Shared modes can be seen as helping to reduce car trips and car dependency.

• New technologies and business models are evolving, and changing how we use the transport system, and how it is being provided.

With the increasing possibilities of information technology that is becoming mobile accessible, geo-specific and real-time, we are seeing an increase in the variety of different mobility services.
We have identified three categories of technological developments or innovative business models that have profoundly evolved in the last five years, and that are likely to lead to a drastic overhaul of the transportation system in the coming decades.

Different modes of shared mobility
Shared mobility refers to all services that give users “short-term access to transportation modes on an ‘as-needed’ basis” (Shaheen et al., 2015). It ranges from ‘traditional’ services such as car-sharing, carpooling, micro-transit and bicycle-sharing to more recent services, such as on-demand ride services. In broader definitions, it also includes the ICT that enables the implementation of these services (Shaheen et al., 2015).

Within these market segments, key recent developments are:

  1.  “One-way free-floating car sharing”: where cars can be returned anywhere within a geo-fenced area.
  2.  “Ride-sourcing” (or “Transportation Network Company” or TNC) services: which use smartphone apps to connect passengers and drivers in real-time. The drivers usually drive their personal vehicle and work (for profit) on a part-time basis. As a result of the competitive pressure from these services, traditional taxi companies are increasingly using matching apps as well.
  3.  Specialised Internet services (including the major TNCs): which now connects potential car-poolers in “peer-to-peer ridesharing” systems.
  4.  The combination of mobile applications and GPS enables the implementation of “dynamic ridesharing”, where routes are adapted in real-time to pick up additional passengers with similar itineraries. Such services are not only provided by “carpool matchers”, but also by TNCs and some traditional taxi firms. These technologies can also improve the efficiency of Demand Response Transit, which plays an important role in reducing mobility poverty.

Versus public transport and car ownership
Research has shown that people often use shared solutions to replace car trips. However, shared solutions may also be a substitute for public transport as well as for a privately owned car, especially in zero-car households. Even if the shared solution is a shared bicycle rather than a shared car, the outcome can be negative, because lower transit use could reduce its financial viability in some areas. The arguments on this particular point, however, tend to vary widely, depending on the region and time period under evaluation.

Nevertheless, “shared” solutions are becoming increasingly well suited to solve the first/last mile problem in public transport. The “first/last mile” problem is known to have a dramatic effect on door-to-door travel time, and is therefore an important barrier to a shift from private car use to public transport. An increasing number of public transport companies and agencies therefore cooperate with TNCs to take advantage of the strong points of TNCs (such as the high door-to-flexibility) to complement their own strong points (such as their capacity to move large quantities of people).

A key enabler of the rise of “shared mobility” has been the development of mobile trip planning apps, which provide the information needed in order to plan a journey, and provide information on possible alternative solutions such as multi-modal trips or trips involving shared mobility. Such apps are also increasingly used for electronic ticketing.

The logical next step in “shared mobility” is the move to Mobility as a Service (MaaS). Kamargianni et al. (2015) define the concept as follows:
The term “Mobility as a Service” stands for buying mobility services based on consumers’ needs instead of buying the means of transport. Via “Mobility as a Service” systems consumers can buy mobility services that are provided by the same or different operators by using just one platform and a single payment. The platform provides an intermodal journey planner, a booking system, a single payment method (single payment for all transport modes), and real time information.

It is also expected that the roll-out of MaaS could lead to higher shares of sustainable modes. However, we need to keep in mind that, compared to the general population, users of shared mobility tend to be well-educated, young adults, living as single-person or childless-couple households, living in middle or middle/upper income households, living in carless or single-car households, living in urban neighbourhoods, and that they are already relatively heavy users of non-car forms of urban transport (e.g. public transport, walking and cycling). People who use “shared mobility” services may thus be very different from the “average” citizen, and the behavioural changes observed amongst early adopters (such as decreased use of private cars) may therefore not be representative for what is achievable in the general population.

Electric mobility
Alternatives to the internal combustion engine (ICE), and especially electric vehicles (EV), are likely to break through in the next two decades, particularly driven by the increased range of electric batteries and cheaper electric mobility.

Currently, electric cars are likely to be better adapted for car sharing than for car ownership. Indeed, as most car sharing trips take place over short distances within urban environments, range limitations or concerns are likely to be less of a barrier in these situations. Moreover, the higher acquisition costs of electric cars matter less if the vehicles are shared, and their lower variable costs give them a competitive advantage if they have a high annual mileage (as shared cars do).

Automated mobility
Prototypes of driverless vehicles are now being tested in operational circumstances by several major players. Currently, the technology needed for full automation is still too expensive to enable a large market share. The rate at which the cost of Automated Vehicles (AVs) will decrease is highly uncertain, but it is generally expected that they will not gain high market shares before the mid-2030s.

The potential benefits of AVs include increased traffic safety, better use of travel time and decreased congestion. AVs would also provide mobility services to people currently unable to drive, for example due to age or handicaps.

As AVs would not need to be parked, significant amounts of urban areas could be freed for other uses if AVs are shared (SAVs). The reduced need for parking space could imply a dramatic change in the urban landscape. Another key advantage is that SAVs can be adapted to the number of passengers (“right sizing”). As a result, manufacturers can build smaller and lighter vehicles, or larger vehicles that will have higher occupancy rates. Even more energy could be saved through platooning of vehicles and efficient traffic flow (and thus less sporadic acceleration and braking).

SAVs may also be better suited for electrification, for instance, because they can be dispatched to only serve trips within a certain range.

On the downside, after having dropped their passengers at their destination, AVs will have to reposition themselves to either park (maybe outside the city centre) or to collect a new passenger (in the case of SAVs). Moreover, due to the reduced opportunity cost of the time spent in traffic, people will likely tolerate longer travel times, and especially longer commuting trips. These elements could lead to dramatic increases in vehicle distance travelled and energy use, and to more urban sprawl.

Simulations have suggested that two conditions will need to be fulfilled to limit the possible negative impacts of automated vehicles:

  • A widespread adoption of dynamic ridesharing.
  • Maintaining (or developing) high capacity public transport (trains, metro lines, Bus Rapid Transit).

The net effects of AVs on energy use, however, could range from more than 90% fuel savings to more than 150% increase in energy use, depending on the dominating factors.

Public policy
A strong case can be made that three important developments in the mobility sector have the potential to be mutually reinforcing, and lead to profound changes in our mobility systems. The uncertainty concerning the net impacts of shared mobility solutions and of automated vehicles implies that the correct pricing of transport will become more important in the future rather than less important. Moreover, the pricing of distance travelled will need to be coordinated with the pricing of other services, such as parking and vehicle-to-grid services. Other policies than pricing are also important, though, such as car sharing, which often requires active support measures from public authorities (such as making parking space available for “one way” systems). Government could also promote the modes that “complement” car sharing, for instance by expanding investments in pedestrian and cycling infrastructure, and by providing the necessary infrastructure of bike-, ride- and car-sharing in the neighbourhood of public transport hubs.

A key question will be whether policies can be designed that harness the strengths of shared mobility solutions to solve the “first/last” mile problem, and thus to promote alternative to unimodal car mobility. The concept of Mobility as a Service fits within this pattern. “Traditional” public transport can create partnerships with TNCs for those areas where the density of the population is too low to justify ‘traditional’ public transport. The technologies underlying shared mobility modes can also be used to reduce mobility poverty through increased performance of demand responsive services.

However, there are definitely some niches where shared solutions are likely to outperform traditional public transport services. Moreover, the rise of AVs will reduce the opportunity cost of time spent in car travel, and this will further undermine the competitive position of some transit services. Therefore, transit will probably increasingly concentrate on the task where it has the biggest competitive advantage: moving huge quantities of people from one transport hub to the other. Whether this can only be implemented by metro, light rail, or BRT systems, or whether traditional bus services still have a role to play in such a landscape, is likely to depend on local factors.

  • Kamargianni, M., Matyas, M., Li, W. & Schäfer, A. (2015), Feasibility study for “Mobility as a Service” concept in London, Funded by DfT Transport Technology Research Innovations Grant (T-­‐TRIG)
  • https://www.bartlett.ucl.ac.uk/energy/docs/fs-maas-compress-final
  • Shaheen, S., Chan, N., Bansal, A. & Cohen, A. (2015a), Shared Mobility: Definitions, Industry Developments, and Early Understanding Bikesharing, Carsharing, On-Demand Ride Services, Ridesharing, Shared-Use Mobility

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